import numpy as np
import plotly.express as px
import plotly.graph_objects as go
from sklearn.linear_model import LinearRegression

df = px.data.tips()
import plotly.graph_objects as go

# Create random data with numpy
import numpy as np
np.random.seed(1)

N = 100
random_x = np.linspace(0, 1, N)
random_y0 = np.random.randn(N) + 5
random_y1 = np.random.randn(N)
random_y2 = np.random.randn(N) - 5

fig = go.Figure()
# Add traces
fig.add_trace(go.Scatter(x=random_x, y=random_y0, mode='markers', name='markers'))
fig.add_trace(go.Scatter(x=random_x, y=random_y1, mode='lines+markers', name='lines+markers'))
fig.add_trace(go.Scatter(x=random_x, y=random_y2, mode='lines', name='lines'))
fig.show()



